def test_label():
"""Test plotting of label."""
_set_backend()
subject_id = "fsaverage"
hemi = "lh"
surf = "inflated"
brain = Brain(subject_id, hemi, surf)
view = get_view(brain)
extra, subj_dir = _get_extra()
brain.add_label("BA1" + extra)
check_view(brain, view)
brain.add_label("BA1" + extra, color="blue", scalar_thresh=.5)
label_file = pjoin(subj_dir, subject_id, "label",
"%s.MT%s.label" % (hemi, extra))
brain.add_label(label_file)
brain.add_label("BA44" + extra, borders=True)
brain.add_label("BA6" + extra, alpha=.7)
brain.show_view("medial")
brain.add_label("V1" + extra, color="steelblue", alpha=.6)
brain.add_label("V2" + extra, color="#FF6347", alpha=.6)
brain.add_label("entorhinal" + extra, color=(.2, 1, .5), alpha=.6)
brain.set_surf('white')
brain.show_view(dict(elevation=40, distance=430), distance=430)
with pytest.raises(ValueError, match='!='):
brain.show_view(dict(elevation=40, distance=430), distance=431)
# remove labels
brain.remove_labels('V1' + extra)
assert 'V2' + extra in brain.labels_dict
assert 'V1' + extra not in brain.labels_dict
brain.remove_labels()
assert 'V2' + extra not in brain.labels_dict
brain.close()
def test_label():
"""Test plotting of label."""
_set_backend()
subject_id = "fsaverage"
hemi = "lh"
surf = "inflated"
brain = Brain(subject_id, hemi, surf)
brain.add_label("BA1")
brain.add_label("BA1", color="blue", scalar_thresh=.5)
subj_dir = utils._get_subjects_dir()
label_file = pjoin(subj_dir, subject_id, "label", "%s.MT.label" % hemi)
brain.add_label(label_file)
brain.add_label("BA44", borders=True)
brain.add_label("BA6", alpha=.7)
brain.show_view("medial")
brain.add_label("V1", color="steelblue", alpha=.6)
brain.add_label("V2", color="#FF6347", alpha=.6)
brain.add_label("entorhinal", color=(.2, 1, .5), alpha=.6)
brain.set_surf('white')
# remove labels
brain.remove_labels('V1')
assert_in('V2', brain.labels_dict)
assert_not_in('V1', brain.labels_dict)
brain.remove_labels()
assert_not_in('V2', brain.labels_dict)
brain.close()
def test_label():
"""Test plotting of label."""
_set_backend()
subject_id = "fsaverage"
hemi = "lh"
surf = "inflated"
brain = Brain(subject_id, hemi, surf)
brain.add_label("BA1")
brain.add_label("BA1", color="blue", scalar_thresh=.5)
subj_dir = utils._get_subjects_dir()
label_file = pjoin(subj_dir, subject_id,
"label", "%s.MT.label" % hemi)
brain.add_label(label_file)
brain.add_label("BA44", borders=True)
brain.add_label("BA6", alpha=.7)
brain.show_view("medial")
brain.add_label("V1", color="steelblue", alpha=.6)
brain.add_label("V2", color="#FF6347", alpha=.6)
brain.add_label("entorhinal", color=(.2, 1, .5), alpha=.6)
brain.set_surf('white')
# remove labels
brain.remove_labels('V1')
assert_in('V2', brain.labels_dict)
assert_not_in('V1', brain.labels_dict)
brain.remove_labels()
assert_not_in('V2', brain.labels_dict)
brain.close()
def test_label():
"""Test plotting of label."""
_set_backend()
subject_id = "fsaverage"
hemi = "lh"
surf = "inflated"
brain = Brain(subject_id, hemi, surf)
view = get_view(brain)
extra, subj_dir = _get_extra()
brain.add_label("BA1" + extra)
check_view(brain, view)
brain.add_label("BA1" + extra, color="blue", scalar_thresh=.5)
label_file = pjoin(subj_dir, subject_id,
"label", "%s.MT%s.label" % (hemi, extra))
brain.add_label(label_file)
brain.add_label("BA44" + extra, borders=True)
brain.add_label("BA6" + extra, alpha=.7)
brain.show_view("medial")
brain.add_label("V1" + extra, color="steelblue", alpha=.6)
brain.add_label("V2" + extra, color="#FF6347", alpha=.6)
brain.add_label("entorhinal" + extra, color=(.2, 1, .5), alpha=.6)
brain.set_surf('white')
brain.show_view(dict(elevation=40, distance=430), distance=430)
with pytest.raises(ValueError, match='!='):
brain.show_view(dict(elevation=40, distance=430), distance=431)
# remove labels
brain.remove_labels('V1' + extra)
assert 'V2' + extra in brain.labels_dict
assert 'V1' + extra not in brain.labels_dict
brain.remove_labels()
assert 'V2' + extra not in brain.labels_dict
brain.close()
def make_brain_figures(srcdf, measure, cinfo, filepat_base, top=5):
views = {'rh': ['medial', 'lateral'],
'lh': ['lateral', 'medial']}
toplabels = {}
for hemi in ['lh', 'rh']:
brain = Brain('fsaverage', hemi, 'inflated', cortex='low_contrast',
subjects_dir=sv.subjects_dir, background='w',
foreground='k')
sv.show_labels_as_data(srcdf, measure, brain,
time_label=None, parc=parc, **cinfo)
if top:
ind = srcdf.index.get_level_values('label').map(
lambda x: x.startswith(hemi[0].upper()))
topl = srcdf[ind].abs().sort_values(
measure, ascending=False).head(top)
topl = (
topl[(topl[measure] != 0)
& topl[measure].notna()]
.index.droplevel('time'))
toplabels[hemi] = topl
alllabels = mne.read_labels_from_annot(
'fsaverage', parc=parc, hemi=hemi)
brain.remove_labels()
for label in alllabels:
if label.name in topl:
brain.add_label(label, borders=1, hemi=hemi, alpha=0.8,
color='k')
# increase font size of colorbar - this only works by increasing the
# colorbar itself and setting the ratio of colorbar to text
brain.data['colorbar'].scalar_bar.bar_ratio = 0.35
brain.data['colorbar'].scalar_bar_representation.position = [0.075, 0.01]
brain.data['colorbar'].scalar_bar_representation.position2 = [0.85, 0.12]
filepat = os.path.join(figdir, filepat_base + '_{}.png'.format(hemi))
brain.save_montage(filepat, views[hemi], colorbar=0)
brain.close()
infiles = [
os.path.join(figdir, filepat_base + '_{}.png'.format(hemi))
for hemi in ['lh', 'rh']]
outfile = os.path.join(figdir, filepat_base + '.png')
os.system("montage -tile 2x1 -geometry +0+0 {} {}".format(
' '.join(infiles), outfile))
return toplabels
def save_groups_labels_figures():
labels, groups = get_groups()
for group in groups:
print(group)
if len(get_group_labels(group)) < 4:
group_label = [l for l in labels if group in l]
colors = get_spaced_colors(len(group_label))
brain = Brain(subject, hemi, surf, offscreen=False)
for label_id, label in enumerate(group_label):
print(label)
brain.add_label(label, color=colors[label_id])
fol = os.path.join(subjects_dir, subject, 'label', '{}_figures'.format(aparc_name))
if not os.path.isdir(fol):
os.mkdir(fol)
brain.save_imageset(os.path.join(fol, group), get_views(), 'jpg')
brain.remove_labels()
brain.close()
def show_labels(srcfile,
measure,
brain=None,
r_name=None,
src_df=None,
transform=None,
surface='white',
time=0.17,
labels=None):
parc = re.match('source_(\w+)_allsubs_\d+_slabs_\w+.h5',
srcfile).group(1)
if labels is None:
labels = mne.read_labels_from_annot('fsaverage',
parc=parc,
hemi='both')
labels = {l.name: l for l in labels}
file = os.path.join(bem_dir, srcfile)
if srcfile.find('_slabs_') >= 0:
slabsi = file.find('slabs_')
r_n = file[slabsi + 6:-3]
if r_name is None:
r_name = r_n
elif r_name != r_n:
raise ValueError(
"Provided source file name and name of desired "
"regressor are not compatible!")
if src_df is None:
src_df = pd.read_hdf(file, 'second_level_src')
if brain is None:
brain = Brain('fsaverage',
'both',
surface,
cortex='low_contrast',
subjects_dir=subjects_dir)
else:
brain.remove_labels(hemi='rh')
brain.remove_labels(hemi='lh')
data = src_df.loc[(slice(None), time), measure]
if transform is not None:
data = transform(data)
vmin = 0.9
norm = matplotlib.colors.Normalize(vmin, 1, clip=True)
alpha = matplotlib.colors.Normalize(vmin, (1 - vmin) / 2 + vmin,
clip=True)
data = data[data > vmin]
cmap = matplotlib.cm.hot
print(data)
for index, value in data.iteritems():
if index[0].startswith('L'):
hemi = 'left'
else:
hemi = 'right'
print(index[0])
brain.add_label(labels[index[0]],
color=cmap(norm(value)),
alpha=alpha(value),
hemi=hemi)
return brain
surf = "pial"
subjects_dir = os.environ.get('SUBJECTS_DIR', '/home/noam/subjects/mri')
# x=range(15)
# cm = plt.get_cmap('jet')
# cNorm = matplotlib.colors.Normalize(vmin=min(x) vmax=max(x))
# return cmx.ScalarMappable(norm=cNorm, cmap=cm)
def get_spaced_colors(n):
HSV_tuples = [(x * 1.0 / n, 0.5, 0.5) for x in range(n)]
RGB_tuples = map(lambda x: colorsys.hsv_to_rgb(*x), HSV_tuples)
return RGB_tuples
labels = glob.glob(
os.path.join(subjects_dir, subject_id, 'label', 'aparc250',
'*{}.label'.format(hemi)))
groups = set([l.split('/')[-1].split('_')[0] for l in labels])
brain = Brain(subject_id, hemi, surf, offscreen=True)
for group in groups:
group_label = [l for l in labels if group in l]
colors = get_spaced_colors(len(group_label))
for label_id, label in enumerate(group_label):
print(label)
brain.add_label(label, color=colors[label_id])
brain.save_imageset('{}-{}'.format(subject_id, group),
['med', 'lat', 'ros', 'caud'], 'jpg')
break
brain.remove_labels()
print('sdf')
def brain_plot(brain,
wname,
toplabels=False,
save=False,
backface_culling=True):
if r_name in ['dot_x', 'dot_y', 'dot_x_sign']:
views = {
'rh':
['medial',
'parietal'], #{'azimuth': -20, 'elevation': 62, 'roll': -68}],
'lh': ['parietal', 'medial']
}
elif r_name in ['sum_dot_x', 'response']:
views = {'rh': ['medial', 'lateral'], 'lh': ['lateral', 'medial']}
if type(brain) is str:
hemi = brain
brain = Brain('fsaverage',
hemi,
'inflated',
cortex='low_contrast',
subjects_dir=sv.subjects_dir,
background='w',
foreground='k')
else:
hemi = brain.geo.keys()[0]
if common_color_scale:
cinfo = get_colorinfo(avsrcdf)
else:
cinfo = get_colorinfo(results[wname]['avsrcdf'])
sv.show_labels_as_data(results[wname]['avsrcdf'],
show_measure,
brain,
time_label=None,
parc=parc,
**cinfo)
if backface_culling:
brain.data['surfaces'][0].actor.property.backface_culling = True
if toplabels:
brain.remove_labels()
alllabels = mne.read_labels_from_annot('fsaverage',
parc=parc,
hemi=hemi)
for label in alllabels:
if label.name in results[wname]['toplabels'][hemi]:
brain.add_label(label,
borders=1,
hemi=hemi,
alpha=0.8,
color='k')
if backface_culling:
for ldict in brain._label_dicts.values():
ldict['surfaces'][0].actor.property.backface_culling = True
# increase font size of colorbar - this only works by increasing the
# colorbar itself and setting the ratio of colorbar to text
brain.data['colorbar'].scalar_bar.bar_ratio = 0.35
brain.data['colorbar'].scalar_bar_representation.position = [0.075, 0.01]
brain.data['colorbar'].scalar_bar_representation.position2 = [0.85, 0.12]
if save:
filepat = os.path.join(figdir,
filepat_base + '_{}_{}.png'.format(wname, hemi))
brain.save_montage(filepat, views[hemi], colorbar=0)
return brain
